With the advancement, ease of use, and decline of prices for digital cameras, the number of digital photographs and images throughout the world has increased enormously. Very often, the digital photographs and images are not completely satisfactory. Indeed, many computer aided techniques exist to manipulate, retouch, or otherwise edit digital photographs and images.
The success of these techniques has led the image processing industry to realize that users would like additional, more sophisticated techniques for editing their digital images. One technique sought after is the ability to distinguish or segment the foreground or subject of an image from the background. The difficult aspect of this technique is creating universal methods for determining the foreground or subject of any image. Some have decided to provide a partial solution (See e.g., Yu and Shi, “Object-Specific Figure-Ground Segmentation”, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Proceedings, Volume 2, pages 39-45, which is hereby incorporated by reference herein in its entirety), but those solutions are not broad enough to solve the general problem of creating a system or method that would run effectively on any image. The major hurdle for creating such a system or method is the difficulties associated with having a computer perform the perceptual and psychological analyses a human brain performs when an image is seen.
As should be apparent, there is an unfulfilled need for systems and methods which would be able to distinguish or segment the foreground or subject of an image from the background. Further, there is an unfulfilled need for systems and methods for utilizing a computer to perform such a figure-ground segmentation in a manner that parallels human perception by using perceptual information.